Related papers: Exploiting Massive D2D Collaboration for Energy-Ef…
Merging mobile edge computing with the dense deployment of small cell base stations promises enormous benefits such as a real proximity, ultra-low latency access to cloud functionalities. However, the envisioned integration creates many new…
Despite the numerous benefits brought by Device-to-Device (D2D) communications, the introduction of D2D into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum…
Motivated by the proliferation of Internet-of-Thing (IoT) devices and the rapid advances in the field of deep learning, there is a growing interest in pushing deep learning computations, conventionally handled by the cloud, to the edge of…
Collaborative edge computing addresses the resource constraints of individual edge nodes by enabling resource sharing and task co-processing across multiple nodes. To fully leverage the advantages of collaborative edge computing, joint…
In this paper, we investigate the coexistence of two technologies that have been put forward for the fifth generation (5G) of cellular networks, namely, network-assisted device-to-device (D2D) communications and massive MIMO (multiple-input…
Edge machine learning can deliver low-latency and private artificial intelligent (AI) services for mobile devices by leveraging computation and storage resources at the network edge. This paper presents an energy-efficient edge processing…
To keep pace with the rapid growth of mobile traffic demands, dense deployment of small cells in millimeter wave (mmWave) bands has become a promising candidate for next generation wireless communication systems. With a greatly increased…
This paper proposes a new power control and pilot allocation scheme for device-to-device (D2D) communication underlaying a multi-cell massive MIMO system. In this scheme, the cellular users in each cell get orthogonal pilots which are…
The design of the forthcoming fifth generation (5G) system shall meet the severe requirement of managing an always increasing amount of traffic generated by both humans and machines, while guaranteeing data security. Among the enabling…
In this paper, we study an energy efficiency maximization problem in uplink for D2D communications underlaid with cellular networks on multiple bands. Utilizing stochastic geometry, we derive closed-form expressions for the average sum…
We formulate and solve the energy minimization problem for a clustered device-to-device (D2D) network with cache-enabled mobile devices. Devices are distributed according to a Poisson cluster process (PCP) and are assumed to have a surplus…
This paper proposes a novel joint computation and communication cooperation approach in mobile edge computing (MEC) systems, which enables user cooperation in both computation and communication for improving the MEC performance. In…
We present a framework for performance optimization in serverless edge-cloud platforms using dynamic task placement. We focus on applications for smart edge devices, for example, smart cameras or speakers, that need to perform processing…
This paper proposes a spectrum selection scheme and a transmit power minimization scheme for a device-to-device (D2D) network cross-laid with a cloud radio access network (CRAN). The D2D communications are allowed as an overlay to the CRAN…
This study addresses the challenge of resource scheduling optimization in edge-cloud collaborative computing using deep reinforcement learning (DRL). The proposed DRL-based approach improves task processing efficiency, reduces overall…
Edge computing technology has great potential to improve various computation-intensive applications in vehicular networks by providing sufficient computation resources for vehicles. However, it is still a challenge to fully unleash the…
The transformation of smart mobility is unprecedented--Autonomous, shared and electric connected vehicles, along with the urgent need to meet ambitious net-zero targets by shifting to low-carbon transport modalities result in new traffic…
Swarm robotics is envisioned to automate a large number of dirty, dangerous, and dull tasks. Robots have limited energy, computation capability, and communication resources. Therefore, current swarm robotics have a small number of robots,…
This paper addresses the challenge of energy efficiency management faced by intelligent IoT devices in complex application environments. A novel optimization method is proposed, combining Deep Q-Network (DQN) with an edge collaboration…
This dissertation studies different aspects of D2D communications and its impact on the key performance indicators of the network. We design an architecture for the collaboration of cellular users by means of timely exploited D2D…